Leverage Point · Data Commons
Vertrauenswürdige, geteilte Erkenntnisse für gemeinsamen Wohlstand
Generative KI erweitert, was wir wissen und tun können. Die Integrität von Daten und wie wir sie steuern, ist wichtiger denn je.
Die Prämisse
Vertrauen schaffen durch bewusste Datenverknüpfung
In einer Welt, die von synthetischen Inhalten und fragmentierten Informationen geprägt ist, hängt koordiniertes Handeln von Datensystemen ab, die vertrauenswürdig, transparent und geteilt sind. Die grossen Herausforderungen von SIPI anzugehen erfordert das Zusammenführen vielfältiger Datenquellen – Gesundheit, Umwelt, Arbeit und mehr. Daten zusammenzuführen reicht jedoch allein nicht aus.
Heute gibt es viele Datenkollaborativen, doch sie verfolgen zu selten eine gemeinsame Richtung und erzeugen so Rauschen statt handlungsleitende Erkenntnisse. Verbindungen müssen bewusst gestaltet werden – geleitet von bedeutsamen Fragen und einem verantwortungsvollen Umgang mit Daten und KI.
Erkenntnisprioritäten
100 Questions Topic Map
In Zusammenarbeit mit The GovLab und der Swiss Data Alliance arbeitet SIPI daran, eine gemeinsame Evidenzgrundlage für das langfristige Wohlbefinden der Schweiz aufzubauen.
The questions and mapping presented here are an initial exploration. Far from being definitive, they illustrate the kind of work needed to guide collective action.
Disclaimer: The map presented herein has been generated with AI-assistance and is yet to be verified.
Which population-level dietary and activity interventions reduce cardiometabolic risk in Swiss working-age adults?
How does air quality variation across Swiss cantons correlate with cardiometabolic risk trajectories?
What biomarker combination best predicts 10-year cardiometabolic risk in Swiss midlife populations?
Can claims data combined with GP records identify high-risk individuals 3–5 years before hospitalisation?
What occupational stressors best predict burnout-related sick leave in Swiss healthcare workers?
What validated tools distinguish stress-related cognitive symptoms from neurodegenerative patterns?
Can GP records, wearables, and claims analytics identify MCI 2–4 years before presentation?
What proportion of burnout absence is preceded by detectable cognitive load signals in the prior 6 months?
Which clinical markers best predict frailty onset in 60–75 year olds in Swiss integrated care settings?
Can hospital discharge data identify patients on frailty trajectories before first avoidable readmission?
What is the economic return on a 1-year delay in frailty onset?
Which community-based interventions most effectively delay dependency in 70–80 year olds?
What proportion of emergency psychiatric presentations could have been averted with earlier stepped-care?
What design features of Swiss integrated care pilots most consistently reduce avoidable hospitalisation?
What reimbursement structures most effectively incentivise prevention-oriented practice without cream-skimming?
What proportion of clinician documentation time can be recovered through AI tools without quality loss?
What governance safeguards are necessary for AI risk stratification in Swiss primary care?
Can federated AI models trained on Swiss hospital data identify risk signals invisible to individual sites?
What evidence threshold do insurers require to participate in shared-savings for prevention in Switzerland?
Which LAMal revision levers have greatest potential to shift incentives toward prevention?
What is the expected ROI of CHF 1M in prevention infrastructure at Lighthouse Region scale over 10 years?
What minimum true cost indicators can food companies credibly report without new data collection?
How does the true cost differential between healthy and unhealthy convenient food vary across Swiss income deciles?
Can a standardised health-adjusted earnings metric for Swiss food companies be derived from existing datasets?
What dietary pattern data best predicts cardiometabolic risk in Swiss 40–60 year olds?
What is the DALY reduction attributable to a 10% improvement in dietary quality across the Swiss working-age population?
Does nutritional density predict frailty onset trajectory independent of physical activity in 60–75 year olds?
Does dietary pattern in Swiss midlife predict cognitive trajectory independent of cardiometabolic risk?
What dietary biomarkers most reliably predict neuroinflammation risk in 50–70 year olds?
Can gut microbiome composition serve as an actionable early indicator of cognitive vulnerability in primary care?
What agricultural practices in Swiss cantons most reliably improve nutritional density of food produced?
Is there a measurable difference in mineral density between Swiss organic and conventional food?
What cantonal agricultural subsidy levers best incentivise higher nutritional density production?
Under what conditions do choice architecture interventions produce durable dietary change?
What employer subsidy reallocation designs most effectively shift cafeteria purchasing toward nutritious options?
Can Digital Product Passports displaying true cost change procurement decisions by institutional buyers?
What is the cost-of-illness reduction from measurable dietary quality improvement over 10 years?
Under what conditions would Swiss insurers participate in shared-savings linked to dietary improvements?
What nutritional interventions most effectively reduce sarcopenia risk in 65–80 year olds?
Swiss Food and Nutrition Valley (SFNV) — topic map across food innovation, nutritional science, sustainability, digital food tech, health and prevention, ingredients and processing, policy and regulation, and talent and ecosystem development. Three levels: cluster → research question → specific topic. Cross-links to SIPI missions shown in gold.
Startup ecosystem
Incubation and acceleration programmes for Swiss food tech startups
Scale-up pathways
Market access and internationalisation for Swiss food innovators
Open innovation
Collaborative R&D between industry, academia, and SMEs
Nutrient bioavailability
How food processing and preparation affect nutrient absorption and efficacy
Health claims regulation
EFSA and Swiss substantiation pathways for nutrition and health claims
Personalised nutrition
Individual-level dietary recommendations based on genetics, microbiome, and lifestyle data
Environmental footprint
Life cycle assessment and planetary boundaries in Swiss food production
Alternative proteins
Plant-based, fermentation-derived, and cultivated protein sources for the Swiss market
Food waste reduction
Interventions reducing food loss across the Swiss supply chain
AI & data in food
Machine learning applications across the food value chain from farm to consumer
Traceability & transparency
Blockchain, IoT, and digital passports for food origin and quality verification
Precision fermentation
Microbial engineering for ingredients, flavours, and functional nutrients at commercial scale
Diet-disease prevention
Evidence-based dietary strategies for chronic disease prevention in Swiss populations
Gut health & immunity
Microbiome, prebiotics, and immune function — evidence and product development implications
Cognitive performance nutrition
Nutritional strategies supporting brain function, focus, and stress resilience
Functional ingredients
Bioactive compounds with demonstrated health-promoting properties and market potential
Clean label & minimal processing
Reformulation strategies meeting consumer demand for shorter ingredient lists
Swiss terroir & heritage
Regional Swiss ingredients and traditional food knowledge in modern applications
Swiss food law
LDAl, OSAV, and regulatory frameworks governing food products in Switzerland
Public health nutrition policy
BAG, cantonal health offices, and national dietary recommendations in practice
EU Green Deal & Farm to Fork
Switzerland's positioning relative to the EU food system transformation agenda
Workforce & skills
Education pipelines and skills gaps across the Swiss food innovation sector
Cluster & network development
SFNV's role in convening and internationalising the Swiss food ecosystem
Consumer engagement & trust
Building public understanding and trust in food innovation and novel ingredients
Fokus 2026
Wohin sich die Datenarbeit dieses Jahr bewegt.
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Kantonale Föderations-Pilotprojekte
Die ersten kantonalen Föderations-Pilotprojekte aufbauen — Gesundheits- und Agrardatensätze über datenschutzfreundliche Brücken und gemeinsame Verknüpfungen von Umwelt-Produktdeklarationen verbinden, unter Governance-Protokollen, die jeden Datensatz bei seinem Verwalter belassen und die Erkenntnisse dennoch teilbar machen.
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Integration von Forschung und Kantonen
Das Data Commons in konkrete kantonale Partnerschaften und Forschungskonsortien einbetten — Gesundheitsämter, Landwirtschaftsstellen und Universitätsteams rund um gemeinsame Fragen zusammenbringen, damit föderierte Evidenz direkt in Beschaffungs-, Präventions- und Politikentscheide einfliesst.
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Offene Methodik und Peer-Review
Die Echtkostenrechnung und die Föderations-Protokolle als offene, peer-reviewte öffentliche Güter veröffentlichen — die Methodik einer unabhängigen Begutachtung unterziehen und die Fähigkeit der Partner aufbauen, sie ohne SIPI in der Schleife zu betreiben.